Method for detecting defects in a substrate having a semiconductor device thereon

ABSTRACT

An inspection apparatus and a method for detecting defects in a substrate having a semiconductor device thereon are provided. The method includes establishing a first inspection region including first patterns repeatedly formed in a first direction and a second inspection region including second patterns repeatedly formed in a second direction on the substrate, determining a first unit inspection size of the first inspection region and a second unit inspection size of the second inspection region, obtaining images of the first and second patterns by moving the substrate in the first direction, and detecting defects in the first and second inspection regions by comparing the obtained images of portions of the first and second inspection regions, respectively, with each other. The first inspection size and second inspection size function as comparison units if defects are detected. The substrate may face an image receiving member.

PRIORITY STATEMENT

This application claims the benefit of priority under 35 U.S.C. §119 toKorean Patent Application No. 2007-4688, filed on Jan. 16, 2007 in theKorean Intellectual Property Office (KIPO), the contents of which areincorporated herein by reference in their entirety.

BACKGROUND

1. Field

Example embodiments relate to a method for detecting defects in asubstrate having a semiconductor device thereon. Other exampleembodiments relate to a method for detecting defects in a substratehaving a semiconductor device thereon using a less complex processwithin a shorter amount of time.

2. Description of the Related Art

As processes for manufacturing a semiconductor device become morecomplex and critical dimensions of semiconductor devices decrease,problems may occur such as defects (e.g., bridges) between semiconductorpatterns, breaking of the semiconductor patterns, voids in thesemiconductor patterns, etc.

A process for detecting defects generated during processes formanufacturing a semiconductor device may be performed after performingeach unit process thereof. If the detection process is accuratelyperformed, successive processes may be performed without defects,preventing a decrease in a yield rate.

Comparison algorithms for detecting defects in a semiconductor devicemay be classified as a random mode algorithm or an array mode algorithm.

A random mode uses a die-to-die method in which a target die to beinspected is compared to an adjacent die. In the random mode, a firstregion of the target die may be compared to a second region of theadjacent die, which corresponds to the first region. If pixels in thefirst region are found to be different from those in the second region,defects may be present. In the random mode, corresponding regionsbetween adjacent dies are compared with each other in order to detectdefects in a region having irregular patterns therein and defects in aregion having regular or repeated patterns therein. If defects aredetected in the random mode, noise may increase due to a colordifference or a focus difference between the adjacent dies. As the noiseincreases, detection power decreases.

In an array mode, images of repeated patterns on a die may be comparedto one another at a predetermined interval. If a difference is found inthe images of the repeated patterns, defects may be present. That is, apixel having the different images may have defects. In the array mode,adjacent patterns on a die are compared to one another in order todetect defects in a region having the repeated patterns therein.

There are seldom color differences or focus differences between theadjacent patterns such that defects may be detected in the array modemore accurately than the random mode because adjacent regions, in whichthe repeated patterns are formed in one die, are compared to one anotherin the array mode. The signal-to-noise ratio (SNR) of the array mode maybe about 1.5 times higher than that of the random mode. Minute defectsmay be accurately detected in the array mode due to the higher SNRthereof. Defects in a substrate having a highly-integrated semiconductordevice thereon are usually detected using the array mode because thedetection power of the array mode is higher than that of the randommode.

A semiconductor device may include a first region where patterns arerepeatedly formed along an x-axis direction and a second region wherepatterns are repeatedly formed along a y-axis direction. The first andsecond regions, in which repetitive patterns are formed in differentdirections from each other, are inspected.

A substrate having a semiconductor device thereon is scanned in thex-axis direction with an image sensor so that images are obtained offirst repetitive patterns in a first region, in which the firstrepetitive patterns are formed in the x-axis direction. The obtainedimages of the first repetitive patterns are compared to one another atpredetermined intervals so that defects in the first region may bedetected. After rotating the substrate by about 90 degrees in the sameplane, the substrate is scanned in the y-axis direction with the imagesensor so that images are obtained of second repetitive patterns in asecond region, in which the second repetitive patterns are formed in they-axis direction. The obtained images of the second repetitive patternsare compared to one another at predetermined intervals so that defectsin the second region may be detected.

A time delay integration (TDI) sensor chip used in the array mode may bearranged in such a way that images of patterns may be obtained only in ascanning direction. As such, defects may be detected in a region wherethe patterns are repeatedly formed in the scanning direction. Aninspection time may be longer if defects of the substrate are detectedusing the array mode, in which patterns are repeatedly formed on thesubstrate in the x-axis and y-axis directions, because the substrate isscanned in each of the x-axis and y-axis directions in order to detectthe defects.

A peripheral portion of the region, in which the repetitive patterns areformed, may have a shape different from that of another portion of theregion. As such, detecting defects in the peripheral portion of theregion may be difficult using the array mode, in which images of therepetitive patterns in one portion of the region are compared to thoseof another portion of the region.

SUMMARY

Example embodiments relate to a method for detecting defects in asubstrate having a semiconductor device thereon. Other exampleembodiments relate to a method for detecting defects in a substratehaving a semiconductor device thereon using a less complex processwithin a shorter amount of time.

According to example embodiments, there is provided a method ofdetecting defects in a substrate having a semiconductor device. A firstinspection region, in which first patterns are repeatedly formed in afirst direction, and a second inspection region, in which secondpatterns are repeatedly formed in a second direction, may be established(or determined) in the substrate. A first unit inspection size of thefirst inspection region may be established (or determined). The firstinspection size functions as a first comparison unit if defects aredetected. A second unit inspection size of the second inspection regionmay be established (or determined). The second inspection size functionsas a second comparison unit if defects are detected. Images of the firstand second patterns in the first and second inspection regions,respectively, may be obtained by moving the substrate in the firstdirection. The substrate faces an image receiving member. Defects in thefirst inspection region may be detected by comparing the images inportions of the first inspection region with each other, wherein each ofthe portions has the first unit inspection size. Defects in the secondinspection region may be detected by comparing the images in portions ofthe second inspection region with each other, wherein each of theportions has the second unit inspection size.

According to example embodiments, a first image in a first portion ofthe first inspection region may be obtained. Second and third images insecond and third portions of the first inspection region may beobtained. Each of the first, second and third portions may have thefirst unit inspection size. The second and third portions may beadjacent to the first portions in the first direction. Gray levels ofthe first, second and third images may be compared by observing thedifference in the pixels. A first difference between the gray level ofthe first image and the gray level of the second image may becalculated. A second difference between the gray level of the firstimage and the gray level of the third image may be calculated. It may bedetermined that a first position of the first portion has defects if thefirst and second differences of a pixel of the first image(corresponding to the first position) are over a predetermined value.

According to example embodiments, the first inspection region mayinclude a portion of a cell region and a sense amplifier (SA) region ofthe semiconductor device. According to example embodiments, a centralportion of the cell region may be set as the first inspection region anda peripheral portion of the cell region may be set as the secondinspection region.

According to example embodiments, for detecting the defects in thesecond inspection region, a fourth image in a fourth portion of thesecond inspection region may be obtained. Fifth and sixth images infifth and sixth portions of the second inspection region may beobtained. Each of the fourth, fifth and sixth portions may have thesecond unit inspection size. The fifth and sixth portions may beadjacent to the fourth portions in the second direction. Gray levels ofthe fourth, fifth and sixth images may be ascertained by comparing thepixels. A third difference between the gray level of the fourth imageand the gray level of the fifth image and a fourth difference betweenthe gray level of the fourth image and the gray level of the sixth imagemay be calculated. It may be determined that a second position of thefourth portion has a defect if the third and fourth differences of apixel in the fourth image (corresponding to the second position) areover a predetermined value.

According to example embodiments, the second inspection region mayinclude a split word line driver (SWD) region of the semiconductordevice.

In some example embodiments, the method may include setting a region inwhich patterns are irregularly formed as a non-inspection region in thesubstrate.

According to example embodiments, obtaining the images in the first andsecond inspection regions may include obtaining images of patterns inportions of the first and second inspection regions along a first lineby moving the substrate in the first direction until an edge of thesubstrate faces an image receiving member. Each of the portions may havea predetermined width. Each of the portions may obtain images ofpatterns in portions of the first and second inspection regions along asecond line by moving the substrate in the first direction until an edgeof the substrate faces the image receiving member. The second line maybe adjacent to the first line.

According to example embodiments, the defects of the first inspectionregion may be immediately detected using the images obtained while thesubstrate is moving in the first direction.

According to example embodiments, the defects in the second inspectionregion may be detected after obtaining images of patterns in theportions of the first and second inspection regions, wherein a sum ofthe portions have the second unit inspection size.

According to example embodiments, the method may include collecting andsynthesizing defects in the first and second inspection regions toindicate defect positions in the first and second inspection regions ofthe substrate, respectively.

According to other example embodiments, the second direction may besubstantially perpendicular to the first direction.

According to example embodiments, an inspection process performed on asubstrate, in which defects of the substrate are detected, by scanningthe substrate only in one direction. Defects in a peripheral portion ofa cell block may be detected using an array mode. As such, the defectsin the substrate may be detected with accuracy within a decreased amountof time.

BRIEF DESCRIPTION OF THE DRAWINGS

Example embodiments will be more clearly understood from the followingdetailed description taken in conjunction with the accompanyingdrawings. FIGS. 1-5 represent non-limiting, example embodiments asdescribed herein.

FIG. 1 is a diagram illustrating a perspective view of an inspectionapparatus for detecting defects in a substrate in accordance withexample embodiments;

FIG. 2 is a flowchart illustrating a method of detecting defects in asubstrate in accordance with example embodiments;

FIG. 3 is a diagram illustrating a plan view of a portion of a cellregion of a memory device in accordance with example embodiments;

FIG. 4 is a diagram illustrating an enlarged plan view of an edgeportion of a cell block of the cell region in FIG. 3; and

FIG. 5 is a diagram illustrating an enlarged plan view of a firstinspection region and a second inspection region of the memory device inFIG. 3.

DETAILED DESCRIPTION OF EXAMPLE EMBODIMENTS

Various example embodiments will now be described more fully withreference to the accompanying drawings in which some example embodimentsare shown. In the drawings, the thicknesses of layers and regions may beexaggerated for clarity.

Detailed illustrative embodiments are disclosed herein. However,specific structural and functional details disclosed herein are merelyrepresentative for purposes of describing example embodiments. Thisinvention may, however, may be embodied in many alternate forms andshould not be construed as limited to only example embodiments set forthherein.

Accordingly, while example embodiments are capable of variousmodifications and alternative forms, embodiments thereof are shown byway of example in the drawings and will herein be described in detail.It should be understood, however, that there is no intent to limitexample embodiments to the particular forms disclosed, but on thecontrary, example embodiments are to cover all modifications,equivalents, and alternatives falling within the scope of the invention.Like numbers refer to like elements throughout the description of thefigures.

It will be understood that, although the terms first, second, etc. maybe used herein to describe various elements, these elements should notbe limited by these terms. These terms are only used to distinguish oneelement from another. For example, a first element could be termed asecond element, and, similarly, a second element could be termed a firstelement, without departing from the scope of example embodiments. Asused herein, the term “and/or” includes any and all combinations of oneor more of the associated listed items.

It will be understood that when an element is referred to as being“connected” or “coupled” to another element, it can be directlyconnected or coupled to the other element or intervening elements may bepresent. In contrast, when an element is referred to as being “directlyconnected” or “directly coupled” to another element, there are nointervening elements present. Other words used to describe therelationship between elements should be interpreted in a like fashion(e.g., “between” versus “directly between,” “adjacent” versus “directlyadjacent,” etc.).

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of exampleembodiments. As used herein, the singular forms “a,” “an” and “the” areintended to include the plural forms as well, unless the context clearlyindicates otherwise. It will be further understood that the terms“comprises,” “comprising,” “includes” and/or “including,” when usedherein, specify the presence of stated features, integers, steps,operations, elements and/or components, but do not preclude the presenceor addition of one or more other features, integers, steps, operations,elements, components and/or groups thereof.

It will be understood that, although the terms first, second, third etc.may be used herein to describe various elements, components, regions,layers and/or sections, these elements, components, regions, layersand/or sections should not be limited by these terms. These terms areonly used to distinguish one element, component, region, layer orsection from another region, layer or section. Thus, a first element,component, region, layer or section discussed below could be termed asecond element, component, region, layer or section without departingfrom the scope of example embodiments.

Spatially relative terms, such as “beneath,” “below,” “lower,” “above,”“upper” and the like, may be used herein for ease of description todescribe one element or a relationship between a feature and anotherelement or feature as illustrated in the figures. It will be understoodthat the spatially relative terms are intended to encompass differentorientations of the device in use or operation in addition to theorientation depicted in the Figures. For example, if the device in thefigures is turned over, elements described as “below” or “beneath” otherelements or features would then be oriented “above” the other elementsor features. Thus, for example, the term “below” can encompass both anorientation which is above as well as below. The device may be otherwiseoriented (rotated 90 degrees or viewed or referenced at otherorientations) and the spatially relative descriptors used herein shouldbe interpreted accordingly.

Example embodiments are described herein with reference tocross-sectional illustrations that are schematic illustrations ofidealized embodiments (and intermediate structures). As such, variationsfrom the shapes of the illustrations as a result, for example, ofmanufacturing techniques and/or tolerances, may be expected. Thus,example embodiments should not be construed as limited to the particularshapes of regions illustrated herein but may include deviations inshapes that result, for example, from manufacturing. For example, animplanted region illustrated as a rectangle may have rounded or curvedfeatures and/or a gradient (e.g., of implant concentration) at its edgesrather than an abrupt change from an implanted region to a non-implantedregion. Likewise, a buried region formed by implantation may result insome implantation in the region between the buried region and thesurface through which the implantation may take place. Thus, the regionsillustrated in the figures are schematic in nature and their shapes donot necessarily illustrate the actual shape of a region of a device anddo not limit the scope.

It should also be noted that in some alternative implementations, thefunctions/acts noted may occur out of the order noted in the figures.For example, two figures shown in succession may in fact be executedsubstantially concurrently or may sometimes be executed in the reverseorder, depending upon the functionality/acts involved.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which example embodiments belong. Itwill be further understood that terms, such as those defined in commonlyused dictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

In order to more specifically describe example embodiments, variousaspects will be described in detail with reference to the attacheddrawings. However, the present invention is not limited to exampleembodiments described.

Example embodiments relate to an inspection device and a method fordetecting defects in a substrate having a semiconductor device thereon.Other example embodiments relate to an inspection device and a methodfor detecting defects in a substrate having a semiconductor devicethereon using a less complex process within a shorter amount of time.

FIG. 1 is a diagram illustrating a perspective view of an inspectionapparatus for detecting defects in a substrate in accordance withexample embodiments.

Referring to FIG. 1, an inspection apparatus 100 includes a stage 102,an imaging unit 110 and a defect detection unit 112.

A substrate W including a plurality of patterns for forming asemiconductor device may be mounted on the stage 102. A driving part(not shown) for moving the stage 102 may be connected to the stage 102.The stage 102 may be moved forward/backward and left/right and rotatedby the driving part.

The imaging unit 110 takes pictures of the substrate W on the stage 102and obtains images showing gradations in the substrate W. The defectdetection unit 112 detects defects from the obtained images of thesubstrate W.

The imaging unit 110 may include a light source 104, an optical system106 and an image sensor 108.

The light source 104 generates light and emits the light. The opticalsystem 106 guides the light emitted from the light source 104 onto thesubstrate W. The optical system 106 receives light reflected from thesubstrate W and incident thereon. The image sensor 108 converts an imageof the substrate W formed by the incident light of the optical system106 into an electrical signal. The image sensor 108 outputs image dataof patterns observed on the substrate W. Time delay integration (TDI)sensor chips (not shown) may be fixedly disposed (or formed) at theimage sensor 108. Images of the patterns of a semiconductor device onthe substrate W may be obtained from the image sensor 108 by moving thesubstrate W in a direction in which the TDI sensor chips are arranged.

The defect detection unit 112 may include a memory part, a detectingpart and/or a processing part. The memory part may include an inspectionregion memory, an inspection size memory and an image data memory. Theinspection region memory may establish and store an inspection region ofa semiconductor device. The inspection size memory may store the unitsize of a portion of the inspection region, wherein one portion of theinspection region having the unit size may be compared to anotherportion of the inspection region having the same size. The image datamemory may store images obtained from the inspection region.

The detecting part may detect defects by comparing the obtained imagesto one another. The processing part may include a microcomputer having acentral processing unit (CPU), which performs various kinds ofoperations (e.g., calculations), a memory device storing various kindsof information, etc.

A plurality of inspection regions (which vary according to a directionin which patterns are repeatedly formed) may be established and storedin the inspection region memory. For example, a region where patternsare repeatedly formed in a first direction may be established as a firstinspection region and a region where patterns are repeatedly formed in asecond direction may be established as a second inspection region.

The inspection size memory may store the size of each of the inspectionregions or portions thereof, wherein each of the repetitive patterns isformed in a portion of the inspection region having the same size. Thestored size may be referred to as a unit inspection size.

If the detecting part detects defects, the portions of a region of asemiconductor device having the unit inspection size are compared to oneanother. A specific portion of the region that is different from otherportions may be considered to have defects. Portions of the region thatare compared to others may be reduced as the unit inspection sizebecomes larger such that the inspection process may be performed in ashorter amount of time than the conventional art.

The image data memory may store images obtained from the inspectionregions. Images obtained from different inspection regions may be storedin different storage regions.

The detecting part compares a first image of a first portion of aninspection region having the unit inspection size with second and thirdimages of second and third portions of the inspection region,respectively, having the unit inspection size and being adjacent to thefirst portion.

The processing part calculates a difference between the gray level ofthe first image and the gray level of the second image. The processingpart calculates a difference between the gray level of the first imageand the gray level of the third image. The processing part may considera pixel, which corresponds to an image having a difference in graylevels over a predetermined value, to have defects.

Hereinafter, a method of detecting defects in a substrate in accordancewith example embodiments will be described with reference to FIGS. 1 to5.

FIG. 2 is a flowchart illustrating a method of detecting defects in asubstrate in accordance with example embodiments.

In step S10, a substrate having patterns thereon may be loaded on astage 102. The patterns may form a memory device (e.g., a dynamic randomaccess memory (DRAM) device, a flash memory device or the like). Animaging unit for obtaining images of the substrate may be disposed (orformed) over the substrate.

The memory device formed on the substrate may include a cell regionincluding a plurality of unit cells and a peripheral region enclosingthe cell region in which peripheral circuits are formed. A columndecoder and a row decoder may be formed in a core region formed betweenthe cell regions.

FIG. 3 is a diagram illustrating a plan view of a portion of a cellregion of a memory device. FIG. 4 is a diagram illustrating an enlargedplan view of an edge portion of a cell block of the cell region in FIG.3.

Referring to FIGS. 3 and 4, a plurality of cell blocks 202 may be formedin a cell region 200. A split word line driver (SWD) region 204, a senseamplifier (SA) region 206 and a connection region 208 may be formedbetween the cell blocks 202. The SWD region 204 may be formed betweenthe cell blocks 202 formed in a first direction. The SA region 206 maybe formed between the cell blocks formed in a second directionsubstantially perpendicular to the first direction. The connectionregion 208 may be formed at a portion of the cell region in which theSWD region 204 and the SA region 206 intersect with each other.

FIG. 5 is a diagram illustrating an enlarged plan view of a firstinspection region and a second inspection region of the memory device inFIG. 3.

Referring to FIGS. 2 and 5, in step 12, a first inspection region 300where first patterns are repeatedly formed in the first direction and asecond inspection region 302 where second patterns are repeatedly formedin the second direction in the memory device on the substrate W may beestablished in the inspection region memory. The first and seconddirections may be substantially perpendicular to each other.

According to example embodiments, the first inspection region 300, inwhich a plurality of patterns is repeatedly formed in the firstdirection, may have a portion of the cell block 202 excluding aperipheral portion of the cell block 202 and the SA region 206. Thesecond inspection region, in which a plurality of patterns is repeatedlyformed in the second direction, may include the peripheral portion ofthe cell block 202 and the SWD region 204. The first and secondinspection regions 300 and 302 may be set to include a plurality ofregions having different sizes.

The first inspection region 300 may not include the peripheral portionof the cell block 202. As such, the first inspection region 300 may havea size smaller than that of the cell block region 202.

According to example embodiments, an edge of the first inspection region300 may be distant from an edge of the cell block 202. The edge of thefirst inspection region 300 may be about 0.3 μm to about 1 μm from theedge of the cell block 202. If another cell block is not formed near theedge of the cell block 202, repetitive patterns are not formed near theedge of the cell block 202. As such, defects may not be detected in theperipheral portion of the cell block 202 using an array mode.

If patterns are repeatedly formed in the peripheral portion of the cellblock 202 in the second direction, defects in the peripheral portion ofthe cell block 202 may be detected because the second inspection region302 includes the peripheral portion of the cell block 202.

A non-inspection region 304 may include a portion of the cell region, inwhich repetitive patterns are not regularly formed. An inspectionprocess may not be performed on the non-inspection region 304. Thenon-inspection region 304 may include the connection region 208, inwhich connection patterns for connecting peripheral circuits to eachother are formed.

In step S14, a first unit inspection size 320 of the first inspectionregion 300 functioning as a comparison unit in an inspection process maybe established. Patterns, included in one portion of the firstinspection region 300, having the first unit inspection size 320 mayhave substantially the same shape as that of other patterns included inanother portion of the first inspection region 300 having the first unitinspection size 320.

The first inspection region 300 may include different sub-regions of thememory device. The first unit inspection sizes 320 of the sub-regionsmay be different from each other.

In step S16, a second unit inspection size 322 of the second inspectionregion 302 functioning as a comparison unit in an inspection process maybe established. Patterns, included in one portion of the secondinspection region 302, having the second unit inspection size 322 mayhave substantially the same shape as that of other patterns included inanother portion of the second inspection region 302 having the secondunit inspection size 322.

The second inspection region 302 may include different sub-regions ofthe memory device. The second unit inspection sizes 322 of thesub-regions may be different from each other.

In step S18, images of patterns in the first and second inspectionregions 300 and 302 may be obtained by moving the substrate W in thefirst direction with an image receiving member facing the substrate W.Images of the substrate W may be formed by the optical system 106. Theimages may be converted into electrical signals by the image sensor 108so that image information may be obtained. The image information may becontinuously generated by moving the stage 102 on which the substrate Wis mounted in the first direction with the stage 102 facing the opticalsystem 106.

The stage 102 moves along the first direction (e.g., from left to right)until an edge of the substrate W faces (or is aligned with) the opticalsystem 106. Images of the patterns having a predetermined width on thesubstrate W may be obtained along a first line. The stage 102 moves inthe opposite direction along the first direction (e.g., from right toleft) until an edge of the substrate W faces (or is aligned with) theoptical system 106. Images of patterns having the predetermined width onthe substrate W may be obtained along a second line adjacent (orparallel) to the first line. If the stage 102 moves along the secondline, the stage 102 moves in the opposite direction along the firstdirection (e.g. the opposite direction to that in which the stage 102moves along the first line). As such, scanning the substrate W along thefirst and second lines may be performed in opposite directions. Forexample, if the substrate W is scanned from left to right to obtainimages of the substrate W along the first line, the substrate W may bescanned from right to left to obtain images of the substrate W along thesecond line. Image information of the whole substrate W may be obtainedby moving the stage 102 in the first direction (and in the reversedirection to the first direction) and obtaining images. Images of thepatterns in the first and second inspection regions 300 and 302 may beeach stored in the image data memory.

In step S20, images of patterns in a portion of the first inspectionregion 300 having the first unit inspection size 320 may be compared toimages of other portions of the first inspection region 300 having thefirst unit inspection size 320 in order to detect defects in the firstinspection region 300.

A first image may be obtained of first patterns in a first portion ofthe first inspection region 300 having the first unit inspection size320. Second and third images may be obtained of second and thirdpatterns in second and third portions of the first inspection region300, respectively. The second and third portions may be adjacent to thefirst portion and have the first unit inspection size 320. The first,second and third patterns may be substantially the same. As such, thefirst second and third images may have substantially the same shape ifdefects do not exist in the first, second or third portions of the firstinspection region 300. The gray level of the first image may be comparedby the pixels to the gray levels of the second and third images,respectively. A difference between the gray level of the first image andthat the gray level of the second image, and a difference between thegray level of the first image and that the gray level of the third imagemay be calculated (or ascertained), respectively. A pixel of the firstimage having a difference in gray levels over a predetermined (orthreshold) value may be considered to have defects.

For example, if defects exist in the first portion of the firstinspection region 300 (that corresponds to the first image) and do notexist in the second or third portions of the first inspection region 300(that correspond to the second and third images, respectively) then afirst gray level difference between the first and second images and asecond gray level difference between the first and third images may besubstantially large. As such, if both of the first and second gray leveldifferences are over a predetermined (or threshold) value, then thefirst portion of the first inspection region 300 may have defects.

Repetitive patterns may be formed in the first inspection region 300 ina direction substantially the same as that in which the substrate Wmoves (i.e., the first direction) if images of the patterns are obtainedin a previous process. After obtaining images when the substrate W ismoving, defects in the first inspection region 300 may be immediatelydetected using the obtained images. As such, defects in the firstinspection region 300 may be detected in real time while the substrate Wis moving.

In step S22, images of patterns in a portion of the second inspectionregion 302 having the second unit inspection size 322 may be compared tothose of other portions of the second inspection region 302 having thesecond unit inspection size 322 in order to detect defects in the secondinspection region 302.

A fourth image may be obtained of fourth patterns in a fourth portion ofthe second inspection region 302 having the second unit inspection size322. Fifth and sixth images may be obtained of fifth and sixth patternsin fifth and sixth portions of the second inspection region 302,respectively. The fifth and sixth portions may be adjacent to the fourthportion and have the second unit inspection size 322. The fourth, fifthand sixth patterns may be substantially the same. As such, the fourth,fifth and sixth images may have substantially the same shape if defectsdo not exist in the fourth, fifth and sixth portions of the secondinspection region 302.

The gray level of the fourth image may be compared by pixel to each ofthe gray levels of the fifth and sixth images. A difference between thegray level of the fourth image and the gray level of the fifth image maybe calculated (or ascertained). A difference between the gray level ofthe fourth image and the gray level of the sixth image may be calculated(or ascertained). A pixel of the fourth image, having a difference inthe gray levels over a predetermined value, may have defects.

For example, if defects exist in the fourth portion of the secondinspection region 302 corresponding to the fourth image and do not existin the fifth and sixth portions of the second inspection region 302corresponding to the fifth and sixth images, a third gray leveldifference between the fourth and fifth images and a fourth gray leveldifference between the fourth and sixth images may be large. As such, ifboth of the third and fourth gray level differences are over apredetermined value, the fourth portion of the second inspection region302 may have defects.

Repetitive patterns may be formed in the second inspection region 302 ina direction substantially perpendicular to that in which the substrate Wis moving (i.e., the second direction) if images of the patterns areobtained in a previous process. Even after obtaining images while thesubstrate W is moving, defects in the second inspection region 302 maynot be immediately detected. After scanning the substrate W in the firstdirection several times, images of the patterns in portions of thesecond inspection region 302 may be obtained wherein the sum of theportions of the second inspection region 302 have the second inspectionsize 322. As such, the defects in the second inspection region 302 maybe detected.

Images in the non-inspection region 304 where patterns of the memorydevice are irregularly formed may not be stored in the image datamemory. Images in the non-inspection region 304, where patterns of thememory device are irregularly formed, may not be used for an inspectionprocess.

In step S24, positions of the defects of the substrate W may beindicated (or identified) by combining the defects in the first andsecond inspection regions 300 and 302.

As illustrated above, defects of a substrate may be detected by scanningthe substrate only in one direction. Defects in a peripheral portion ofa cell block may be detected using an array mode.

According to example embodiments, an inspection process may be performedon a substrate in which defects of the substrate may be detected byscanning the substrate only in one direction such that the amount oftime necessary for performing the inspection may be reduced.

Defects in a peripheral portion of a cell block may be detected using anarray mode in order to detect the defects more accurately. As such,succeeding processes may be performed only if defects do not exist,increasing the yield rate of a semiconductor device.

The foregoing is illustrative of example embodiments and is not to beconstrued as limiting thereof. Although a few example embodiments havebeen described, those skilled in the art will readily appreciate thatmany modifications are possible in example embodiments withoutmaterially departing from the novel teachings and advantages.Accordingly, all such modifications are intended to be included withinthe scope of this invention as defined in the claims. In the claims,means-plus-function clauses are intended to cover the structuresdescribed herein as performing the recited function, and not onlystructural equivalents but also equivalent structures. Therefore, it isto be understood that the foregoing is illustrative of various exampleembodiments and is not to be construed as limited to the specificembodiments disclosed, and that modifications to the disclosedembodiments, as well as other embodiments, are intended to be includedwithin the scope of the appended claims.

1. A method of detecting defects in a substrate, the method comprising:establishing a first inspection region including at least one firstpattern repeatedly formed in a first direction on the substrate, thefirst inspection region including a portion of a cell block, and asecond inspection region including at least one second patternrepeatedly formed in a second direction on the substrate, the secondinspection region including a peripheral portion of the cell block,wherein a semiconductor device is mounted on the substrate; determininga first unit inspection size of the first inspection region, wherein thefirst unit inspection size functions as a first comparison unit ifdefects are detected; determining a second unit inspection size of thesecond inspection region, wherein the second unit inspection sizefunctions as a second comparison unit if defects are detected; obtainingat least one image of the first pattern in the first inspection regionand at least one image of the second pattern in the second inspectionregion by moving the substrate in the first direction, wherein thesubstrate faces an image receiving member; detecting defects in thefirst inspection region by comparing portions of the images obtainedfrom the first inspection region with each other, wherein each of theportions has the first unit inspection size; and detecting defects inthe second inspection region by comparing portions of the imagesobtained from the second inspection region with each other, wherein eachof the portions has the second unit inspection size.
 2. The method ofclaim 1, wherein detecting defects in the first inspection regionincludes: obtaining a first image of a first portion of the firstinspection region, a second image of a second portion of the firstinspection region and a third image of a third portion of the firstinspection region, each of the first, second and third portions havingthe first unit inspection size, wherein the second and third portionsare adjacent to the first portion in the first direction; comparing graylevels of the first, second and third images by each pixel; ascertaininga first difference between the gray level of the first image and thegray level of the second image; ascertaining a second difference betweenthe gray level of the first image and the gray level of the third image;and determining that the first portion has a defect if the first andsecond differences of a pixel in the first image are over apredetermined value.
 3. The method of claim 2, wherein ascertaining thefirst and second differences includes calculating the first and seconddifferences.
 4. The method of claim 2, wherein detecting defects in thesecond inspection region includes: obtaining a fourth image of a fourthportion of the second inspection region, a fifth image of a fifthportion of the second inspection region and a sixth image of a sixthportion of the second inspection region, each of the fourth, fifth andsixth portions having the second unit inspection size, wherein the fifthand sixth portions are adjacent to the fourth portion in the seconddirection; comparing gray levels of the fourth, fifth and sixth imagesby each pixel; ascertaining a third difference between the gray level ofthe fourth image and the gray of the fifth image; and ascertaining afourth difference between the gray level of the fourth image and thegray level of the sixth image; and determining that the fourth portionhas a defect if the third and fourth differences of a pixel in thefourth image are over a predetermined value.
 5. The method of claim 4,wherein ascertaining the third and fourth differences includescalculating the third and fourth differences.
 6. The method of claim 1,wherein the first inspection region includes a portion of a cell regionand a sense amplifier (SA) region of the semiconductor device.
 7. Themethod of claim 6, wherein a central portion of the cell region isestablished as the first inspection region and a peripheral portion ofthe cell region is established as the second inspection region.
 8. Themethod of claim 1, wherein obtaining images of the first and secondinspection regions includes: obtaining images of a first portion of thefirst pattern in the first inspection region along a first line andimages of a first portion of the second pattern in the second inspectionregion along the first line by moving the substrate in the firstdirection until an edge of the substrate is aligned with an imagereceiving member, wherein each of the first portion of the first andsecond patterns has a predetermined width; and obtaining images of asecond portion of the first pattern in the first inspection region alonga second line and images of a second portion of the second pattern inthe second inspection region along the second line by moving thesubstrate in the first direction until an edge of the substrate isaligned with the image receiving member, wherein the second line isadjacent to the first line.
 9. The method of claim 8, wherein thedefects in the first inspection region are immediately detected usingthe images obtained while the substrate is moving in the firstdirection.
 10. The method of claim 8, wherein the defects in the secondinspection region are detected after obtaining the images of the firstand second portions of the first pattern in the first inspection regionand the images of the first and second portions of the second pattern inthe second inspection region, wherein a sum of the first and secondportions of the second pattern in the second inspection region is equalto the second unit inspection size.
 11. The method of claim 1, whereinthe second inspection region includes a split word line driver (SWD)region of the semiconductor device.
 12. The method of claim 1, furthercomprising establishing a region in which patterns are irregularlyformed as a non-inspection region in the substrate.
 13. The method ofclaim 1, further comprising combining the defects detected in the firstand second inspection regions such that defect positions in the firstand second inspection regions of the substrate, respectively, areidentified.
 14. The method of claim 1, wherein the second direction issubstantially perpendicular to the first direction.